code: def test_fpn_block(self, input_param, input_shape, expected_shape):
      net = FeaturePyramidNetwork(**input_param)
      data = OrderedDict()
      data["feat0"] = torch.rand(input_shape[0])
      data["feat1"] = torch.rand(input_shape[1])
      result = net(data)
      self.assertEqual(result["feat0"].shape, expected_shape[0])
      self.assertEqual(result["feat1"].shape, expected_shape[1])
  
file_path: MONAI/tests/test_fpn_block.py
imports: from __future__ import annotations
  import unittest
  from collections import OrderedDict
  import torch
  from parameterized import parameterized
  from monai.networks.blocks.backbone_fpn_utils import _resnet_fpn_extractor
  from monai.networks.blocks.feature_pyramid_network import FeaturePyramidNetwork
  from monai.networks.nets.resnet import resnet50
  from monai.utils import optional_import
  from tests.utils import SkipIfBeforePyTorchVersion, test_script_save
label_desc: Use image node_id 1 for calling the TestFPNBlock obj's underlying member method code with example usage: obj.test_fpn_block(input_param, input_shape, expected_shape) without return types